Completed
Working with reliability buckets
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Implementing End-to-End Demand Forecasting with Databricks and MLflow
Automatically move to the next video in the Classroom when playback concludes
- 1 Outline
- 2 Scope of Project
- 3 Ingesting the files
- 4 Using extra data sources
- 5 Feature Engineering
- 6 Picking a ML model
- 7 Model Granularity
- 8 Making use of parallelism
- 9 Tracking Performance and experiments
- 10 Which metrics to use?
- 11 Working with reliability buckets
- 12 Feeding it back into the client's systems
- 13 Frequency of training and scoring
- 14 Monitoring and Alerting
- 15 Conclusion
- 16 DATA+AI SUMMIT 2022
